Obare DM and Muraya MM. Comparison of Accuracy of Support Vector Machine Model and Logistic Regression Model in Predicting Individual Loan Defaults.
. 2018; 6(6):266-271. doi: 10.12691/AJAMS-6-6-8
loan defaults, prediction model, logistic regression model, support vector machine model
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[1] | Hoque, Z. (2005). Linking Environmental Uncertainty to Non-Financial Performance. The British Accounting Review. Britain. |
|
[2] | Evusa, Z., Mudaki, J. S., & Ojala, D. O. (2015). Evaluation of the Factors Leading to Loan Default at Equity Bank, Kenya. Journal of Economics and Sustainability. ISSN 2224-607X. pp. Vol.6, No.8.2016. |
|
[3] | Lahsana, A., Anion, R. & Wah, T. (2010). “Credit Scoring Models using soft Computing Methods: a survey”. International Arab Journal of Information Technology, 7(2), 115-123. |
|
[4] | Bekhet, H. & Eletter, S. (2014). “Credit Risk Management for the Jordanian Commercial Banks: Neural Scoring Approach”. Review of Development Finance, 4, 20-28. |
|
[5] | Chen, Y., Cheng, C. (2013). “Hybrid Models based on Rough Set Classifiers for Setting Credit Rating Decision Rules in the Global Banking Industry”. Knowledge- Based Systems, 39(1), 224-239. |
|
[6] | Banasik, J., Crook, J. N. and Thomas, L.C. (1999). Not If but When Will Borrowers Default. Journal of the Operational Research Society, 50(12) pp. 1185-1190. |
|
[7] | Stepanova, M., & Thomas, L. (2002). Survival Analysis Methods for Personal Loan Data. Operations Research, 50(2), pp.277-289. |
|
[8] | Tong, E. N., Mues C. & Thomas, L. (2012). Mixture Cure Models in Credit Scoring: If and When Borrowers Default. European Journal of Operational Research, 218(1) pp. 132-139. |
|
[9] | Khandani, A.E., Kim, A.J. & Andrew W. Lo. (2010). Consumer Credit-Risk Models via Machine-Learning Algorithms. Journal of Banking Finance 34:2767-87. |
|
[10] | Galinndo, J., & Pablo T. (2000). Credit Risk Assessment using Statistical and Machine Learning: Basic Methodology and Risk and Risk Modelling Applications. Computational Economics 15: 107-43. |
|
[11] | Butaru F., Qingqing C., Brian C., Sanmay D., Andrew W. Lo. & Akhtar S. (2016). Risk and risk Management in the Credit Card Industry. Journal of Banking and Finance 72:218-39. |
|
[12] | Divino, J. A., Lima, E. S., & Orrillo, J. (2013). Interest Rates and Default in Unsecured Loan Markets. Quantitative Finance, 13(12), 1925-1934. |
|
[13] | Martin, A., Travis L. & Venkatasamy P. (2010). A Framework to Develop Qualitative Bankruptcy Prediction Rules. St. Joseph’s Journal of Humanities and Science 1:73-83. |
|
[14] | Agbemava, E., Nyarko, I. K., Adade, T. C., & Bediako, A. K. (2016). Logistic Regression Analysis of Predictors of Loan Defaults by Customers of Non- Traditional Banks in Ghana. African Journal of Business Management 10(2), 33-43. |
|
[15] | Calabrese, R. & Osmetti, S. A. (2013). Modelling Small and Medium Enterprise Loan Defaults as Rare Events: The Generalized Extreme Value Regression Model. Journal of Applied Statistics, 40(6), 1172-1188. |
|
[16] | Zhou, L., Lai K.K., & Yu. L. (2010). Least Squares Support Vector Machines Ensemble Models for Credit Scoring. Expert Systems with Applications 37: 127-133. |
|
[17] | Sebe, V., Razvan, A. (2009). Estimating Probabilities of Default using Support Vector Machines. A master Thesis Presented at centre of Applied Statistics and Economics. Humbolt University, Berlin. |
|
[18] | Huang, C. L., Chen, M. C., & Wang, C. J. (2007). Credit Scoring with a Data Mining Approach based on Support Vector Machines. Expert systems with Application. 33 (2007). 847-856. |
|
[19] | James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning (Vol. 112). New York: Springer. |
|
[20] | J. Pinheiro, D., Bates, S DebRoy, D., Sarkar, R., C Team R Package Version 3 (57), 1-89. |
|
[21] | Tashakkori, A., & Teddie, C. (2003), The Handbook of Mixed Methods in Social and Behavioural Research, Sage, Thousand Oaks, CA. |
|
[22] | Mugenda, A. & Mugenda, O. (1999). Research Methods-Quantitative and Qualitative Approaches, Nairobi. Act Press. |
|
[23] | Ameyaw-Amankwah,I. (2011). Causes and Effects of Loan Defaults on the Profitability of Okomfo Anokye Rural Bank. Master Thesis KNUST, Accra, Ghana. |
|
[24] | Muller K-R., Mika S., (2001). An Introduction to Kernel-based Learning Algorithms, IEEE Transactions on Neural Networks 12(2), 181-201. |
|