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International Conference on Management Science and Engineering Management

ICMSEM 2017: Proceedings of the Eleventh International Conference on Management Science and Engineering Management pp 78–90Cite as

A Hybrid Model of AdaBoost and Back-Propagation Neural Network for Credit Scoring

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Part of the book series: Lecture Notes on Multidisciplinary Industrial Engineering ((LNMUINEN))

Abstract

Owing to the development of internet finance in China, credit scoring is growing into one of the most important issues in the field of financial risk management. Quantitative credit scoring models are widely used tools for credit risk assessment in financial institutions. In this study, an AdaBoost algorithm model based on back-propagation neural network for credit scoring with high accuracy and efficiency is proposed. We first illustrate the basic concepts of back-propagation neural network and AdaBoost algorithm and propose a hybrid model of AdaBoost and back-propagation neural network, then two real-world credit data sets are selected to demonstrate the effectiveness and feasibility of the proposed model. The results show that the proposed model can get higher accuracy compared to other classifiers listed in this study.

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Acknowledgements

This research was supported by the project of Research Center for System Sciences and Enterprise Development (Grant No.Xq16C03).

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Authors and Affiliations

  1. School of Finance, Southwestern University of Finance and Economics, Chengdu, 611130, People’s Republic of China

    Feng Shen & Xingchao Zhao

  2. Southwestern University of Finance and Economics, Chengdu, 611130, People’s Republic of China

    Dao Lan & Limei Ou

Authors
  1. Feng Shen
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  2. Xingchao Zhao
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  3. Dao Lan
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  4. Limei Ou
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Corresponding author

Correspondence to Feng Shen .

Editor information

Editors and Affiliations

  1. Business and Administration, Sichuan University, Chengdu, China

    Jiuping Xu

  2. Fuzzy Logic Systems Institute, Tokyo University of Science, Tokyo, Tokyo, Japan

    Mitsuo Gen

  3. Azerbaijan National Academy of Sciences, Baku, Azerbaijan

    Asaf Hajiyev

  4. Monash University, Clayton, Victoria, Australia

    Fang Lee Cooke

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Shen, F., Zhao, X., Lan, D., Ou, L. (2018). A Hybrid Model of AdaBoost and Back-Propagation Neural Network for Credit Scoring. In: Xu, J., Gen, M., Hajiyev, A., Cooke, F. (eds) Proceedings of the Eleventh International Conference on Management Science and Engineering Management. ICMSEM 2017. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-59280-0_6

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  • DOI: https://doi.org/10.1007/978-3-319-59280-0_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59279-4

  • Online ISBN: 978-3-319-59280-0

  • eBook Packages: EngineeringEngineering (R0)

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