Risk management is one of the most important branches of business and finance. Classification models are the most popular and widely used analytical group of data mining approaches that can greatly help financial decision makers and managers to tackle credit risk problems. However, the...

This paper deals with the use of fuzzy logic as a support tool for evaluation of corporate client credit risk in a commercial banking environment. It defines possibilistic distribution of soft data used for corporate client credit risk assessment by applying fuzzy logic modeling, with a major...

Banks faced many difficulties related to lax credit standards. The effective management of credit risk is a critical component of a comprehensive approach to risk management and it should maintain credit risk exposure within acceptable parameters. However, the problem arises when standards are...

To evaluate consumer loan applications, loan officers use many techniques such as judgmental systems, statistical models, or simply intuitive experience. In recent years, fuzzy systems and neural networks have attracted the growing interest of researchers and practitioners. This study compares...

Giving loans and issuing credit cards are two of the main concerns of banks in that they include the risks of non-payment. According to the Basel 2 guidelines, banks need to develop their own credit risk assessment systems. Some banks have such systems; nevertheless they have lost a large amount...