References
- Arunkumar, R., & Kotreshwar, G. (2006). Risk management in commercial banks: A case study of public and private sector banks. Indian institute of capital markets, 9th capital markets conference. Retrieved from SSRN http://ssrn.com/abstract=877812
- Bensic, M., Sarlija, N., & Zekic-Susac, M. (2005). Modeling small-business credit scoring by using logistic regression, neural networks and decision trees. Intellectual Systems Accounting and Financial Management, 13(3), 133–9. doi:10.1002/isaf.261
- Boguslauskas, V., & Mileris, R. (2009). Estimation of credit risk by artificial neural networks models. Izinerine EkonomikaEngineering Economics, 4, 1392–2785.
- Cao, Q., & Parry, M. (2009). Neural network earning per share forecasting models: A comparison of backward propagation and genetic algorithm. Decision Support Systems, 47, 32–41. doi:10.1016/j.dss.2008.12.011
- Central Bank of Jordan. 2018. Annual Repot. 47. Amman, Central Bank of Jordan: Jordan.
- Huang, C. L., Chen, M. C., & Wang, C. J. (2007). Credit scoring with a data mining approach based on support vector machines. Experts Systems with Applications, 33, 847–856. doi:10.1016/j.eswa.2006.07.007
- Kandah, A. (2009). Interviews with Jordanian bankers, association of banks in Jordan. Amman, Jordan.
- Keramati, A., & Yousefi, N. (2011). A proposed classification of data mining techniques in credit scoring.International conference on industrial engineering and operations management Kuala Lumpur, Malaysia.
- Lahsana, A., Ainon, R., & Wah, T. (2010). Credit scoring models using soft computing methods: A survey. The International Arab Journal of Information Technology, 7(2), 129–139.
- Limsombunchai, G. V. C., & Lee, M. (2005). Lending decision model for agricultural sector in Thailand,American. Journal of Applied Science, 2(8), 1198–1205.
- Malhorta, R., & Malhorta, D. K. (2003). Evaluating consumer loans using neural networks. Omega, 31(2), 83–96. doi:10.1016/S0305-0483(03)00016-1
- Martens, D., Baesens, B., Gestel, T., & Vanthienen, J. (2007). Comprehensible credit scoring models using rule extraction from support vector machines. European Journal of Operational Research, 183(3), 1466–1476. doi:10.1016/j.ejor.2006.04.051
- Olokoyo, F. (2011). Determinants of commercial banks lending in Nigeria. International of Financial Research, 2(2). doi:10.5430/ijfr.v2n2p61
- Olszak and Ziemba. (2006). Business intelligence systems in the holistic infrastructure development supporting decision-making in organizations. Interdisciplinary Journal of Information, Knowledge, and Management, 1, 47–58.
- Ong, C., Huang, J., & Tzeng, G. (2005). Building credit scoring models using genetic programming. Expert Systems with Applications, 2, 1–7.
- Raghavendra, B. K., & Simha, J. (2010). Evaluation of feature selection methods for predictive modeling using neural networks in credits scoring. The International Journal of Advanced Networking and Applications, 2(3), 714–718.