Gaussian Mixture Support Vector Machines for Credit Scoring

Posted: 24 Apr 2022

See all articles by Saeed Shadkam

Saeed Shadkam

affiliation not provided to SSRN

Shima Saheb

Sharif University of Technology, Graduate School of Management and Economics, Students

Hamid R. Arian

York University

Masoud Talebian

Graduate School of Management and Economics, Sharif University of Technology ; University of Newcastle (Australia)

Date Written: April 4, 2022

Abstract

Credit scoring assesses the risk associated with lending to individuals or institutions and is of great importance. To do the scoring, classification methods, based on machine learning, classify the individuals into creditworthy and uncreditworthy. We utilize both application scoring and behavioral scoring for the classification of different datasets. We apply a novel preprocessing method and also a novel denoising method based on the Gaussian Mixture Model and then combine it with the Support Vector Machines classifier. Our method is specifically useful to treat imbalanced datasets, and our results show that a well-treated balanced dataset improves the standard models significantly. We compare our approach with the standard benchmarks and show a higher overall accuracy.

Keywords: classification, machine learning, preprocessing, denoising, imbalanced datasets

Suggested Citation

Shadkam, Saeed and Saheb, Shima and Arian, Hamid R. and Talebian, Masoud, Gaussian Mixture Support Vector Machines for Credit Scoring (April 4, 2022). Available at SSRN: https://ssrn.com/abstract=4074514

Saeed Shadkam

affiliation not provided to SSRN

Shima Saheb

Sharif University of Technology, Graduate School of Management and Economics, Students ( email )

Tehran
Iran

Hamid R. Arian

York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

HOME PAGE: http://arian.ai

Masoud Talebian (Contact Author)

Graduate School of Management and Economics, Sharif University of Technology ( email )

Tehran
Iran

University of Newcastle (Australia) ( email )

University Drive
Callaghan, NSW 2308
Australia

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