The Effect of Delay Fine on Reducing Delay in Repayment of Loan; Study of Melat Bank’s Branches in Mazandaran

Document Type : Scientific paper

Authors

1 PhD student, Islamic Azad University, Firoozkuh Branch

2 Faculty member of Islamic َAzad ,University, Firoozkuh branch, Firoozkuh, Iran

3 Faculty member of Islamic Azad University, Firoozkuh Branch, Firoozkuh, Iran

4 Faculty member of Islamic Azad University, Firoozkuh Branch, Foroozkuh, Iran

Abstract

Vajholtezam-e-Banki is the amount of money more than the amount of the loan which is defined in Islamic Banking as the fine for defaulting on a loan payment. The purpose of this study is to analyze the effect of delay fine on the probability of delay in repayment of loans. In order to do so, 19999 costumer in Melat Bank’s branches in the Mazandaran province between 2012 and 2018 were studied. The number of branches amounts to 68. The model devised in this study is a one way Panel – Probit. One dimension of the data will be the individuals and the other dimension will be the branches and the time dimension is not included in the model. The results suggest that there is a significant negative relationship between the fine and delay in repayment. Also, the estimations suggest the decreasing effect of income, salary reduction, dividend of payments, and history of delay on repayment. The results of this study are suitable to be devised as a policy complement in other banks and branches in order to take appropriate policy measures for the purpose of decreasing delay in repayment of loans. Also, the findings of the study indicate that this banking concept is in line with Islamic teachings.

Keywords


Agrawal, S. P., Rezaee, Z., & Pak, H. S. (2006). Continuous Improvement: An Activity-Based Model. Management Accounting Quarterly7(3), 14.
Ahangaran, M. & Molakarimi, F. (2001). Theological and Legal Study of Fine. Journal of Islamic Economic. 40(10), 179 – 208. (in Persian).
Ahmadvand, V. (2004). Effects and Regulations of Defining Fine for Delay and Default in Iran’s Law in Comparison with Britain. Mesbah. 53. (in Persian).
Angbazo, L. (1997). Commercial bank net interest margins, default risk, interest-rate risk, and off-balance sheet banking. Journal of Banking & Finance21(1), 55-87.
Bergerès, A. S., d'Astous, P., & Dionne, G. (2015). Is there any dependence between consumer credit line utilization and default probability on a term loan? Evidence from bank-customer data. Journal of Empirical Finance33, 276-286.
Borujerdi, H. (2008). Comprehensive Shiei Verses. Vol 18. Tehran. Green Culture. (in Persian).
Chen, Y. Q., Zhang, J., & Ng, W. W. (2018, July). Loan Default Prediction Using Diversified Sensitivity Undersampling. In 2018 International Conference on Machine Learning and Cybernetics (ICMLC) (Vol. 1, pp. 240-245). IEEE.
Duffie, D., Saita, L., & Wang, K. (2007). Multi-period corporate default prediction with stochastic covariates. Journal of Financial Economics83(3), 635-665.
Eskini, R. (1992). Discource on International Law. Tehran. Sepehr. (in Persian).
Ghalich, V. (2015). New Methods for Overcoming the Challenges of Delay in Banking without Interest. The 26th Conference of Islamic Banking. (in Persian).
Ghari Ibn Eid, M.A. (2005). The Problems of Islamic Banks and Their Solutions. Translation by Gholamreza Mesbahi Moghadam. Islamic Economics. 5(20). (in Persian).
Global Set of Islamic Encyclopedia. The new Information and Search. https://cgie.org.ir. (in Persian).
Golpaygani, M. (1985). Makma-ol-Vasayel. Vol 2. 2nd Edition. Dar-ol-Qoran-e-Karim. (in Persian).
Jiang, C., Wang, Z., Wang, R., & Ding, Y. (2017). Loan default prediction by combining soft information extracted from descriptive text in online peer-to-peer lending. Annals of Operations Research, 1-19.
Jiménez, G., Ongena, S., Peydró, J. L., & Saurina, J. (2009). Credit Availability. Identifying Balance-Sheet Channels with Loan Applications. mimeo.
Katuzian, N. (2003). The Responsibility of Production Flaws. Tehran University’s Publications. (in Persian).
Khazai, M. (2010). Theological – Legal Study of Delay Fine. Fadak. 1(4), 75 – 91. (in Persian).
Makarem Shirazi, N. (2006). Response to the Letter 5/619//56/d dated 9/10/1996, Legal Commission of Majles. (in Persian).
Molakarimi, F. (2015). The Study of Methods for Overcoming the Challenge of Delay in Banking without Interest in Iran with Emphasis on Islamic Banks’ Experience. The 26th Conference of Islamic Banking. (in Persian).
Mousavi Bojnourdi, M. & Omran Zadeh, A. (2016). The Delay Damage in Theology and Law with Focus on Imam Khomeini’s Thoughts. Matin. 18(73), 15 – 34. (in Persian).
Mousavian, S.A. (2006). Theological – Legal Study of Delay Fine in Iran. Theology and Law. (in Persian).
Nazarpour, M. Molakarimi, F. Mehrabi, L. (2016). Substitutes for Delay Fine in Banking without Interest in Iran. Applicable Economic Studies of Iran. 5(19), 241 – 267. (in Persian).
Qian, M., & Hu, F. (2019, April). An Empirical Study on Prediction of the Default Risk on P2P Lending Platform. In IOP Conference Series: Materials Science and Engineering (Vol. 490, No. 6, p. 062048). IOP Publishing.
Rezai, M. (2001). Theological – Legal Study of Delay Fine. Islamic Economics. 2(6). (in Persian).
Sadough. (1992). Islamic Encyclopedia. (in Persian).
Sadathosseini, S. H. (2017). Credit limits of Vajho-l-Tezam from a “amount” point of view in financial liabilities. Theology and Islamic Law Studies. 9(17): 131 – 156. (in Persian).
Salami, H. Ensan, E. (2018). Decomposition of the impact of effective variables on agricultural loan default among different non-current liabilities. Iranian Economic Studies. 23(76): 185 – 217. (in Persian).
Stein, R. M. (2005). The relationship between default prediction and lending profits: Integrating ROC analysis and loan pricing. Journal of Banking & Finance29(5), 1213-1236.
Taskhiri, M. (2005). Punishment in Law. Feghh-e-Ahle Beit. 35. (in Persian).
Tiwari, A. K. (2018). Machine learning application in loan default prediction. Machine Learning4(5).
Tsai, M. C., Lin, S. P., Cheng, C. C., & Lin, Y. P. (2009). The consumer loan default predicting model–An application of DEA–DA and neural network. Expert Systems with applications36(9), 11682-11690.