University of Bahrain
Scientific Journals

Credit Granting Decisions: An Empirical Investigation

Show simple item record Metawa, Saad A. 2018-07-31T05:41:10Z 2018-07-31T05:41:10Z 1997-11-01
dc.identifier.issn 2210-1454
dc.description.abstract Credit granting decisions have received widespread attention over the past two decades. Such popularity is due to the role of credit in financing economic activities. Previous credit granting decision models have used different borrower attributes – quantitative as well as qualitative- as explanatory variables. The results of these models provided insufficient evidence regarding the best set of variables which can be used in the prediction of the likelihood of granting credit. The purpose of this study as to examine the explanatory power of a set of financial attributes in the prediction of the likelihood of granting bank credit. The sample included 89 loan applications reviewed by three leading Bahraini banks during the 1986 – 1990 periods. The loan applications reviewed were limited only to business loans. A linear Probability Model (LPM) was developed to examine the simultaneous effect of the selected key financial ratios on the dependent variable. The results of the study indicated that the likelihood of granting bank credit can be predicted on the basis of the applicants' financial statement data. Furthermore, the results showed that the asset utilization ratio, debt level, debt paying capacity and working capital adequacy all have significant impact on the dependent variable. Finally a Tau statistic was used to compare the percentage of correct classification/ prediction produced by the LPM with those of a chance model. The results of the comparisons indicated that LPM can achieve better classification/ prediction accuracy than the chance model. The empirical evidence drawn from this study provides more support to the increasing role of the quantitative models in improving the managerial decision making process in the various types of organizations in general and in the banking industry in particular. Furthermore, the predictive accuracy of the LPM can be enhanced by adding more explanatory variables other than those used in the study such as cash flows/debt, earning stability, as well as some measures of the general economic conditions. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-ShareAlike 4.0 International *
dc.rights.uri *
dc.subject financing economic
dc.subject Credit Granting Decisions
dc.title Credit Granting Decisions: An Empirical Investigation en_US
dc.type Article en_US
dc.volume 01
dc.issue 01
dc.source.title The Arab Journal of Accounting
dc.abbreviatedsourcetitle AJA

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