A Model for Credit Analysis in Bank of Industry and Mine

Abstract

Resources allocation is considered to be one of the main activities for banks. The most important risk that threatens this activity is commitments refusal on the part of facilities receiver. One of the ways that can be used to benefit properly from investment opportunities and help to stop wasting resources is bankruptcy prediction and default probability. In this research, we have established Multiple Discriminant Analysis (MDA) model to predict the default of the companies which receive facilities and credit. The result of this research, which are based on the information provided by the companies receiving facilities and credit from Industry and Mine Bank, have indicated that, five ratios of the seventeen selected ratios have the most power in distinguishing the group of companies with default and without default. Another result is that there is a trade-off between ROA and default probability and the last conclusion is that the companies with a higher net profit are more successful in repaying their credits and facilities.

Keywords

• default
• credit risk
• multiple discriminant analysis (mda)
• roa
• roe