How to cite this paper
Ghodrati, H & Taghizad, G. (2014). Credit risk assessment: Evidence from banking industry.Management Science Letters , 4(8), 1765-1772.
Refrences
Anderson, R., & Sundaresan, S. (2000). A comparative study of structural models of corporate bond yields: An exploratory investigation. Journal of Banking & Finance, 24(1), 255-269.
Allen, J. C. (1995). A promise of approvals in minutes, not hours. American Banker, 28.
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.
Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 5, 71-111.
Behr, P., & Güttler, A. (2007). Credit risk assessment and relationship lending: An empirical analysis of German small and medium?sized enterprises. Journal of Small Business Management, 45(2), 194-213.
Bennell, J. A., Crabbe, D., Thomas, S., & Gwilym, O. A. (2006). Modelling sovereign credit ratings: Neural networks versus ordered probit. Expert Systems with Applications, 30(3), 415-425.
Berge, T. O., & Boye, K. G. (2007). An analysis of banks & apos; problem loans. Economic Bulletin (Norges Bank), 78(2), 65-76.
Boussabaine, A. H., & Wanoous, M. (2000). A Neurons fuzzy Model for Predicting Business Bankruptcy. In Business Applications of Neural Networks: The State-of-the-Art of Real-World Applications (ed.), 55-69.
Chen, R., Hu, S., & Pan, G. (2006) Default Prediction of Various Structural Models. Rutgers University, National Taiwan University, and National Ping-Tung University of Sciences and Technologies.
Collin?Dufresne, P., & Goldstein, R. S. (2001). Do credit spreads reflect stationary leverage ratios?. The Journal of Finance, 56(5), 1929-1957.
Desai, V. S., Conway, D. G., Crook, J. N., & Overstreet, G. A. (1997). Credit-scoring models in the credit-union environment using neural networks and genetic algorithms. IMA Journal of Management Mathematics, 8(4), 323-346.
Desai, V. S., Conway, D. G., Crook, J. N., & Overstreet, G. A. (1997). Credit-scoring models in the credit-union environment using neural networks and genetic algorithms. IMA Journal of Management Mathematics, 8(4), 323-346.
Dovern, J., Meier, C. P., & Vilsmeier, J. (2010). How resilient is the German banking system to macroeconomic shocks?. Journal of Banking & Finance,34(8), 1839-1848.
Ebrahimi, M., & Daryabar, A. (2012). Credit risk management in bank system- data envelopment analysis approach and logistic and neural system. Invest Knowledge Periodical, 1(2).
Espinoza, R. A., & Prasad, A. (2010). Nonperforming loans in the GCC banking system and their macroeconomic effects. International Monetary Fund.
Feldman, R. (1997). Small business loans, small banks and big change in technology called credit scoring. The Region, (Sep), 19-25.
Gan, C., & Lee, M. (2005). An analysis of credit scoring for agricultural loans in Thailand. American Journal of Applied Sciences, 2(8), 1198.
Goldstein, M., & Turner, P. (1998). Banking crises in emerging economies: origins and policy options. Available at SSRN 52074.
Goukasian, L., & Seaman, S. (2009). Strategies for predicting equipment lease default. Journal of Equipment Lease Financing, 27(1), 1-7.
Habibi, S. (2002). Examining effective factors on bank loan on-time repayment on bank Keshavarzi (agriculture bank). Tehran University, Economic Department, Un-Published Dissertation
Hashemi Nodehi, M.M. (1998). Evaluating causes of past nuisance and banking delayed receivables Bank facilities in bank Maskan, during 65-76. Tehran University, Management Department, Un-Published Dissertation
Iran Supreme Banking Institute/ Islamic republic of Iran central bank (2012). Designing and explaining credit risk model in country banking system. 16thIslamic banking system association.
Isazade, S., & Mansoori Gargary, H. (2009). Credit risk and capacity estimation of Tejarat bank clients via neural network. Basirat periodicals, 42.
Jensen, H. L. (1992). Using neural networks for credit scoring. Managerial Finance, 18(6), 15-26.
Jesus, S., & Gabriel, J. (2006). Credit cycles, credit risk, and prudential regulation.
Keeton, W. R., & Morris, C. S. (1987). Why do banks 7 loan losses differ?. Economic Review, 3-21.
Khodai Vale Zaqerd, M., & Qalami Bavil, S. (2012). Evaluating effective key factors on declination risk of accepted banks in Tehran stockbrokerage market. Stock Brokerage Periodical, 21.
Khoshsima, R., & Soheili Tash, M. (2011). Credit risk, operational risk and liquidity effects on Iran banking system efficiency. Investigatory-scientific periodicals of budget and planning, 4.
Kiss, F. (2003). Credit scoring processes from a knowledge management perspective. Social and Management Sciences, 11(1), 95-110.
Koopman, S. J., & Lucas, A. (2005). Business and default cycles for credit risk. Journal of Applied Econometrics, 20(2), 311-323.
Malhotra, R., & Malhotra, D. K. (2002). Differentiating between good credits and bad credits using neuro-fuzzy systems. European Journal of Operational Research, 136(1), 190-211.
Mansoori, A., & Azar, A. (2012). Designing and explaining efficient model of bank facilities allocation, neural systems approaches, linear logistic regression. Modarres scientific-investigatory, 26.
Mansoori, A. (2003). Designing and explaining mathematical model of bank loan allocation, neural network and classical models approach. Tarbiat Modarres University, Un-Published Dissertation.
Mehrara, M. et al. (2009). Credit ranking of Parsian bank legal clients. Periodicals of Economic Modeling, 3.
Mueller, C. (2000). A simple multi-factor model of corporate bond prices. Available at SSRN 248369.
Najafi, A. (2000). Criticism and exploration of bank’s banking delayed receivables collecting methods from a legal view. University of Tehran, Law Department, Un-Published Dissertation.
Pesaran, M. H., Schuermann, T., Treutler, B. J., & Weiner, S. M. (2006). Macroeconomic dynamics and credit risk: a global perspective. Journal of Money, Credit and Banking, 1211-1261.
Pesola, J. (2005). Banking fragility and distress: An econometric study of macroeconomic determinants. Bank of Finland Research Discussion Paper, (13).
Rahmani, A., & Esmaili, Q. (2009). Neural network efficiency, distinction analysis and logistic regression in predicting declination, Accounting Economy Periodicals, 7(4).
Rambaldi, A. N., Zapata, H. O., & Christy, R. D. (1992). Selecting the best prediction model: An application to agricultural cooperatives. Southern Journal of Agricultural Economics, 24, 163-163.
Sabzevari, H., & Noorbakhsh, I. (2006). Contrustive analysis of logistic parametric credit preferring model via non-parametric method CART. 17th Islamic banking association, Iranian supreme banking Institution.
Tehrani, M., & Fallah, S. (2005). Designing and explaining credit risk model in country banking system. Social and human sciences magazine of Shiraz university, 2(43), 45-46
Vaez, M., Amiri, H., & Haydari, M. (2010). Analyzing commercial cycles effects on Iran banking declination rate and indicating facilities optimized package for total banking system. 21stannual conference of currency and fiscal policies, monetary and economic periodicals, 3(7).
West, D. (2000). Neural network credit scoring models. Computers & Operations Research, 27(11), 1131-1152.
Allen, J. C. (1995). A promise of approvals in minutes, not hours. American Banker, 28.
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.
Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 5, 71-111.
Behr, P., & Güttler, A. (2007). Credit risk assessment and relationship lending: An empirical analysis of German small and medium?sized enterprises. Journal of Small Business Management, 45(2), 194-213.
Bennell, J. A., Crabbe, D., Thomas, S., & Gwilym, O. A. (2006). Modelling sovereign credit ratings: Neural networks versus ordered probit. Expert Systems with Applications, 30(3), 415-425.
Berge, T. O., & Boye, K. G. (2007). An analysis of banks & apos; problem loans. Economic Bulletin (Norges Bank), 78(2), 65-76.
Boussabaine, A. H., & Wanoous, M. (2000). A Neurons fuzzy Model for Predicting Business Bankruptcy. In Business Applications of Neural Networks: The State-of-the-Art of Real-World Applications (ed.), 55-69.
Chen, R., Hu, S., & Pan, G. (2006) Default Prediction of Various Structural Models. Rutgers University, National Taiwan University, and National Ping-Tung University of Sciences and Technologies.
Collin?Dufresne, P., & Goldstein, R. S. (2001). Do credit spreads reflect stationary leverage ratios?. The Journal of Finance, 56(5), 1929-1957.
Desai, V. S., Conway, D. G., Crook, J. N., & Overstreet, G. A. (1997). Credit-scoring models in the credit-union environment using neural networks and genetic algorithms. IMA Journal of Management Mathematics, 8(4), 323-346.
Desai, V. S., Conway, D. G., Crook, J. N., & Overstreet, G. A. (1997). Credit-scoring models in the credit-union environment using neural networks and genetic algorithms. IMA Journal of Management Mathematics, 8(4), 323-346.
Dovern, J., Meier, C. P., & Vilsmeier, J. (2010). How resilient is the German banking system to macroeconomic shocks?. Journal of Banking & Finance,34(8), 1839-1848.
Ebrahimi, M., & Daryabar, A. (2012). Credit risk management in bank system- data envelopment analysis approach and logistic and neural system. Invest Knowledge Periodical, 1(2).
Espinoza, R. A., & Prasad, A. (2010). Nonperforming loans in the GCC banking system and their macroeconomic effects. International Monetary Fund.
Feldman, R. (1997). Small business loans, small banks and big change in technology called credit scoring. The Region, (Sep), 19-25.
Gan, C., & Lee, M. (2005). An analysis of credit scoring for agricultural loans in Thailand. American Journal of Applied Sciences, 2(8), 1198.
Goldstein, M., & Turner, P. (1998). Banking crises in emerging economies: origins and policy options. Available at SSRN 52074.
Goukasian, L., & Seaman, S. (2009). Strategies for predicting equipment lease default. Journal of Equipment Lease Financing, 27(1), 1-7.
Habibi, S. (2002). Examining effective factors on bank loan on-time repayment on bank Keshavarzi (agriculture bank). Tehran University, Economic Department, Un-Published Dissertation
Hashemi Nodehi, M.M. (1998). Evaluating causes of past nuisance and banking delayed receivables Bank facilities in bank Maskan, during 65-76. Tehran University, Management Department, Un-Published Dissertation
Iran Supreme Banking Institute/ Islamic republic of Iran central bank (2012). Designing and explaining credit risk model in country banking system. 16thIslamic banking system association.
Isazade, S., & Mansoori Gargary, H. (2009). Credit risk and capacity estimation of Tejarat bank clients via neural network. Basirat periodicals, 42.
Jensen, H. L. (1992). Using neural networks for credit scoring. Managerial Finance, 18(6), 15-26.
Jesus, S., & Gabriel, J. (2006). Credit cycles, credit risk, and prudential regulation.
Keeton, W. R., & Morris, C. S. (1987). Why do banks 7 loan losses differ?. Economic Review, 3-21.
Khodai Vale Zaqerd, M., & Qalami Bavil, S. (2012). Evaluating effective key factors on declination risk of accepted banks in Tehran stockbrokerage market. Stock Brokerage Periodical, 21.
Khoshsima, R., & Soheili Tash, M. (2011). Credit risk, operational risk and liquidity effects on Iran banking system efficiency. Investigatory-scientific periodicals of budget and planning, 4.
Kiss, F. (2003). Credit scoring processes from a knowledge management perspective. Social and Management Sciences, 11(1), 95-110.
Koopman, S. J., & Lucas, A. (2005). Business and default cycles for credit risk. Journal of Applied Econometrics, 20(2), 311-323.
Malhotra, R., & Malhotra, D. K. (2002). Differentiating between good credits and bad credits using neuro-fuzzy systems. European Journal of Operational Research, 136(1), 190-211.
Mansoori, A., & Azar, A. (2012). Designing and explaining efficient model of bank facilities allocation, neural systems approaches, linear logistic regression. Modarres scientific-investigatory, 26.
Mansoori, A. (2003). Designing and explaining mathematical model of bank loan allocation, neural network and classical models approach. Tarbiat Modarres University, Un-Published Dissertation.
Mehrara, M. et al. (2009). Credit ranking of Parsian bank legal clients. Periodicals of Economic Modeling, 3.
Mueller, C. (2000). A simple multi-factor model of corporate bond prices. Available at SSRN 248369.
Najafi, A. (2000). Criticism and exploration of bank’s banking delayed receivables collecting methods from a legal view. University of Tehran, Law Department, Un-Published Dissertation.
Pesaran, M. H., Schuermann, T., Treutler, B. J., & Weiner, S. M. (2006). Macroeconomic dynamics and credit risk: a global perspective. Journal of Money, Credit and Banking, 1211-1261.
Pesola, J. (2005). Banking fragility and distress: An econometric study of macroeconomic determinants. Bank of Finland Research Discussion Paper, (13).
Rahmani, A., & Esmaili, Q. (2009). Neural network efficiency, distinction analysis and logistic regression in predicting declination, Accounting Economy Periodicals, 7(4).
Rambaldi, A. N., Zapata, H. O., & Christy, R. D. (1992). Selecting the best prediction model: An application to agricultural cooperatives. Southern Journal of Agricultural Economics, 24, 163-163.
Sabzevari, H., & Noorbakhsh, I. (2006). Contrustive analysis of logistic parametric credit preferring model via non-parametric method CART. 17th Islamic banking association, Iranian supreme banking Institution.
Tehrani, M., & Fallah, S. (2005). Designing and explaining credit risk model in country banking system. Social and human sciences magazine of Shiraz university, 2(43), 45-46
Vaez, M., Amiri, H., & Haydari, M. (2010). Analyzing commercial cycles effects on Iran banking declination rate and indicating facilities optimized package for total banking system. 21stannual conference of currency and fiscal policies, monetary and economic periodicals, 3(7).
West, D. (2000). Neural network credit scoring models. Computers & Operations Research, 27(11), 1131-1152.