BEHAVIORAL BIAS, ECONOMIC CONDITIONS, AND INFORMATION TECHNOLOGY: DETERMINANTS OF CREDIT ASSESSMENT IN INDONESIA
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Credit assessment plays a critical role in maintaining financial stability, particularly in emerging economies like Indonesia, where regional disparities in infrastructure and economic development make consistent credit evaluation difficult. Variability in institutional practices, the integration of information technology (IT), and behavioral biases among analysts contribute to inefficiencies and inaccuracies in credit decision-making. This study investigates the extent to which behavioral biases, economic conditions, and IT adoption influence credit assessment outcomes across Indonesian financial institutions. A cross-sectional online survey was conducted between April and October 2024, involving 454 credit analysts from commercial banks, rural banks, cooperatives, and non-bank financial institutions located in all central provinces of Indonesia. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to test both direct and moderating effects among the variables. The results show that economic conditions have a significant direct impact on credit assessment outcomes with an effect size of 0.486. Information technology also demonstrates a positive, though more negligible, direct effect, with an effect size of 0.137. Behavioral biases do not significantly influence credit assessment directly (p = 0.759), but their effect becomes significant when moderated by economic conditions (interaction effect = -0.217, p < 0.001). Information technology does not significantly moderate this relationship (p = 0.885). The findings indicate that the three predictors can explain 59.7% of the variance in credit assessment. These results emphasize the dominant role of economic context and technology over cognitive biases in determining credit evaluation outcomes across Indonesia's financial institutions.
JEL Classification Codes: G21, D81, G32.
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