Building a Credit Scoring Model Based on Data Mining Approaches

Nowadays, one of the biggest challenges in banking sector, certainly, is assessment of the client’s creditworthiness. In order to improve the decision-making process and risk management, banks reso...

[1]  Bart Baesens,et al.  PROFIT MAXIMIZING LOGISTIC REGRESSION MODELING FOR CREDIT SCORING , 2018, 2018 IEEE Data Science Workshop (DSW).

[2]  Mohan Delampady.  Minimum Description Length Methods in Bayesian Model Selection: Some Applications , 2013 .

[3]  Hong Yu,et al.  A Comparative Study on Data Mining Algorithms for Individual Credit Risk Evaluation , 2010, 2010 International Conference on Management of e-Commerce and e-Government.

[4]  Michael Murray,et al.  An experimental comparison of classification techniques in debt recoveries scoring: Evidence from South Africa's unsecured lending market , 2018, Expert Syst. Appl..

[5]  Min-Yuh Day,et al.  A comparative study of data mining techniques for credit scoring in banking , 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

[6]  M. Gholamian,et al.  Utility based Credit Scoring for Banks and Financial Institutions: Case Study of a Major Iranian Bank , 2014 .

[7]  Hussein A. Abdou,et al.  Predicting Creditworthiness in Retail Banking with Limited Scoring Data , 2016, Knowl. Based Syst..

[8]  Deni Memic,et al.  Assessing Credit Default using Logistic Regression and Multiple Discriminant Analysis: Empirical Evidence from Bosnia and Herzegovina , 2015 .

[9]  Prince Kumar Singh,et al.  Prediction analysis of risky credit using Data mining classification models , 2017, 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT).

[10]  Stefan Lessmann,et al.  Extreme learning machines for credit scoring: An empirical evaluation , 2017, Expert Syst. Appl..

[11]  Radu Mutihac,et al.  Functional Neuroimaging Data Mining , 2018 .

[12]  Francisco Javier García Castellano,et al.  Expert Systems With Applications , 2022 .

[13]  Maysam F. Abbod,et al.  A new hybrid ensemble credit scoring model based on classifiers consensus system approach , 2016, Expert Syst. Appl..

[14]  S. Khan,et al.  Lift and Drainage of Electrically Conducting Power Law Fluid on a Vertical Cylinder , 2014 .

[15]  Hedieh Sajedi,et al.  A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring , 2015 .

[16]  Shashi Dahiya,et al.  Credit Scoring Using Ensemble of Various Classifiers on Reduced Feature Set , 2015 .

[17]  M Dilsha.  Model Validation of a Credit Scorecard Using Bootstrap Method , 2014 .

[18]  A. Pérez-Torregrosa,et al.  Big Data techniques to measure credit banking risk in home equity loans , 2018, Journal of Business Research.

[19]  Eiman Kambal,et al.  Credit scoring using data mining techniques with particular reference to Sudanese banks , 2013, 2013 INTERNATIONAL CONFERENCE ON COMPUTING, ELECTRICAL AND ELECTRONIC ENGINEERING (ICCEEE).

[20]  Xin Chen,et al.  Predicting the Severity of Bug Reports Based on Feature Selection , 2018, Int. J. Softw. Eng. Knowl. Eng..

[21]  Jasmina Nalic,et al.  Importance of data pre-processing in credit scoring models based on data mining approaches , 2018, 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).