Credit Risk Prediction Using Artificial Neural Network Algorithm

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Author(s)

Deepak Kumar Gupta 1,* Shruti Goyal 1

1. UCD Michael Smurfit Graduate Business School, Dublin, Ireland

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2018.05.02

Received: 10 Mar. 2018 / Revised: 26 Mar. 2018 / Accepted: 10 Apr. 2018 / Published: 8 May 2018

Index Terms

Credit Risk, Artificial Neural Network, Linear Regression, Credit Risk Analysis, Credit Rating

Abstract

Artificial neural network is an information processing system which is influenced by the human brain and works on the same principles of the biological nervous system. They possess the ability to extract meaning from complex and intricate data, by detecting trends and extracting patterns from it. This paper illustrates the ability of neural network model and linear regression model constructed to predict the creditworthiness of an application accurately and precisely with minimal false predictions and errors. The results are shown to be similar for both the models, thus, models are efficient to use depending on the type of application and attributes.

Cite This Paper

Deepak Kumar Gupta, Shruti Goyal, "Credit Risk Prediction Using Artificial Neural Network Algorithm", International Journal of Modern Education and Computer Science(IJMECS), Vol.10, No.5, pp. 9-16, 2018. DOI:10.5815/ijmecs.2018.05.02

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