Research Opportunities for Neural Networks: The Case for Credit |
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| Authors: | Brad S. Trinkle Amelia A. Baldwin |
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| Affiliation: | 1. Mississippi State University, Adkerson School of Accountancy, PO Box EF, Mississippi State, MS, USA;2. Department of Accounting, Economics, Finance, University of Arkansas–Fort Smith, Fort Smith, AR, USA |
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| Abstract: | This article identifies research opportunities in the use of artificial neural networks in credit scoring and related business intelligence situations, particularly as they have been emerging in the global economy. In the literature review, particular attention is paid to commercial lending credit risk assessment and consumer credit scoring. Investors and auditors need models that can predict whether a customer will stay viable. Lenders must manage their credit risk to maximize profits and cash flow, while minimizing losses. As the global economic recession continues, investors are tightening their investment belts and need models that help them make better investment decisions, while lenders must strengthen lending practices and better identify both good and bad credit risks. Artificial neural networks may help firms improve their credit model development, and thereby their credit decisions and profitability. Such technology may also help improve development in emerging economies. Copyright © 2016 John Wiley & Sons, Ltd. |
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