http://orcid.org/0000-0002-6018-9699
References
- Abe, N., Melville, P., Pendus, C., Reddy, C. K., Jensen, D. L., Thomas, V. P., & Gardinier, T. (2010). Optimizing debt collections using constrained reinforcement learning. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 75–84). Washington, DC: ACM.
- Ayed, E. B., & Ayed, M. B. (2016). A quality model for the evaluation of decision support systems based on a knowledge discovery from data process. Journal of Decision Systems, 25(2), 95–117.10.1080/12460125.2016.1156999
- Beran, J., & Djaidba, A. Y. K. (2007). Credit risk modeling based on survival analysis with immunes. Statistical Methodology, 4(3), 251–276.10.1016/j.stamet.2006.09.001
- Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees. New York, NY: Chapman & Hall/CRC.
- Duman, E., Ekinci, Y., & Tanriverdi, A. (2012). Comparing alternative classifiers for database marketing: The case of imbalanced datasets. Expert Systems with Applications, 39, 48–53.10.1016/j.eswa.2011.06.048
- European Central Bank. (2016). What are non-performing loans (NPLs)? Retrieved from https://www.ecb.europa.eu/explainers/tell-me/html/npl.en.html
- de Filho, A., Mues, C., & Thomas, L. C. (2010). Optimizing the collections process in consumer credit. Production and Operations Management, 19(6), 698–708.10.1111/poms.2010.19.issue-6
- Goodman, J. (1992). Leveraging the customer database to your competitive advantage. Direct Marketing, 55(8), 26–27.
- Ha, S. H., & Krishnan, R. (2012). Predicting repayment of the credit card debt. Computers and Operations Research, 39(4), 765–773.10.1016/j.cor.2010.10.032
- Haughton, D., & Oulabi, S. (1997). Direct marketing modeling with CART and CHAID. Journal of Direct Marketing, 11(4), 42–52.10.1002/(ISSN)1522-7138
- International Monetary Fund (2017). Global financial stability report: Getting the policy mix right. Washington, DC: April.
- Kass, G. (1980). An exploratory technique for ınvestigating large quantities of categorical data. Applied Statistics, 29(2), 119–127.10.2307/2986296
- Miller, G., Weatherwax, M., Gardinier, T., Abe, N., Melville, P., Pendus, C., … Cooley, B. (2012). Tax collections optimization for New York state. Interfaces, 42(1), 74–84.10.1287/inte.1110.0618
- Noh, H. J., Roh, T. H., & Han, I. (2005). Prognostic personal credit risk model considering censored information. Expert Systems with Applications, 28(4), 753–762.
- O’Flaherty, B., & Heavin, C. (2015). Positioning predictive analytics for customer retention. Journal of Decision Systems, 24(1), 3–18.10.1080/12460125.2015.994353
- Quinlan, J. R. (1990). Decision trees and decision making. IEEE Transactions on Systems, Man and Cybernetics, 20(2), 339–346.10.1109/21.52545
- Regina, E. J., & Norman, J. (1999). Survival models and data analysis. New York, NY: Wiley.
- Shao, M., Zoldi, S., Cameron, G., Martin, R., Drossu, R., Zhang, J., & Shoham, D. (2007). Enhancing delinquent debt collection using statistical models of debt historical ınformation and account events. Patent no: US 7,191,150 B1.
- Tong, E. N. C., Mues, C., & Thomas, L. C. (2012). Mixture cure models in credit scoring: If and when borrowers default. European Journal of Operational Research, 218(1), 132–139.