The Existence of Asymmetric Information in Credit Analysis of the Commnity Credit Bank (CCB)

Abstract

Asymmetric information in credit market existence arises when the bank is not able to identify borrower based on the probability of repayment. This situation can cause credit defaults. The high of nonperforming loan in CCB credit market refers to the high of credit defaults which indicate the existence of asymmetric information in CCB credit analysis. This research empirically identifies asymmetric information in CCB credit analysis which the objective is to analyze how the indicators of credit analysis can explain the quality of borrower credit collectability. The hypothesis of the research is the indicators of credit analysis cannot explain the quality of borrower credit collectability.Survey is conducted randomly to 36 of CCB in 6 provinces in Java Island that represent incorporate CCB which member of Indonesian CCB association. Unit analyses of the research are 2.268 borrower bundle credit accounts. Frequency and cross tabulation statistics are used to do descriptive analysis, since binary logistic regression is used to do the verification analysis. Test results showed that less than 20% variation of dependent variables can be explained by 26 independent variables in logistic regression model research. It is stated that the indicators of credit analysis that is used during BPR can only explain less than 20% the quality of borrower credit collectability being good or default. More than 80% variations in the quality of borrower credit collectability can not be precisely described by the indicators of credit analysis in the model. This indicates that the BPR is not able to identify the borrower based on the probability level of credit payments. Analysis of indicators of credit used by the BPR was not able to produce signals that can identify borrowers based on the probability level of credit payments. The results of this study stated that there are asymmetric information on credit analysis of BPR.