Title :
ANN Model for Corporate Credit Risk Assessment
Author :
Dima, Alina Mihaela ; Vasilache, Simona
Author_Institution :
Acad. of Economic Studies, Bucharest, Romania
Abstract :
The paper proposes decision tools to be used by commercial banks in order to classify the companies applying for credits in good and bad creditors, based on the number of days of delay in payment. Probit regression and neural networks, applied to a sample of companies which delayed or not their credit reimbursements are used to orient the decision taken by the bank, consistent with its priorities, of either minimizing the risk, or enlarging the customer base.
Keywords :
artificial intelligence; banking; decision support systems; neural nets; regression analysis; risk management; artificial neural networks; commercial banks; corporate credit risk assessment; credit reimbursements; customer base; decision tools; regression analysis; Algorithm design and analysis; Classification tree analysis; Econometrics; Economic forecasting; Hazards; Logistics; Neural networks; Performance analysis; Predictive models; Risk management; artificial intelligence; credit risk; probit regression;
Conference_Titel :
Information and Financial Engineering, 2009. ICIFE 2009. International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-0-7695-3606-4
DOI :
10.1109/ICIFE.2009.33
