Articles

The Effect of Growth Opportunity and Credit Risk on Firm Value and Profitability as Mediating Variables in Digital Banking

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The digital transformation phenomenon in the Indonesian banking industry is growing rapidly, marked by the emergence of digital banks offering fully technology-based services. This change is driving increased competition and creating new dynamics in assessing company value, particularly regarding growth opportunities and credit risk quality. This study aims to analyze the effect of growth opportunity and credit risk on company value, with profitability as a mediating variable. The study uses a quantitative approach with growth opportunity and credit risk as independent variables, profitability as a mediating variable, and company value as the dependent variable. The research sample consisted of six digital banks selected through purposive sampling with a total of 30 observations during the 2020–2024 period. Data were obtained from the companies’ annual financial reports and official publications of the Indonesia Stock Exchange. Then, they were processed using panel regression with the EGLS method and the Sobel test using the Eviews 12 application. The results show that growth opportunity has a positive and significant effect on company value, while credit risk has a negative and significant effect. Credit risk also has a negative and significant effect on profitability, while growth opportunity has no significant effect on profitability. Furthermore, profitability has a positive and significant effect on company value, but does not mediate the relationship between growth opportunity and credit risk on company value. These findings suggest that the firm value of digital banks is more influenced by growth prospects and asset quality than the mediating pathway through profitability.

Development of a Character Evaluation Model in Risk Management for Microfinance in Individuals of Small Medium Enterprise

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This study develops a character evaluation model for PT.XYZ’s customers in microfinance credit risk management. Integrating psychological and industrial engineering approaches, this research assesses customer personality using the International Personality Item Pool Big-Five Factor Marker-25 (IPIP BFM-25). The five personality dimensions, which are Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism, are assessed to classify customers according to their credit risk level. Decision Tree is employed for the classification of customers into risk groups, and the latter are represented graphically with Traffic Light Analysis (TLA) color codes green (low risk), yellow (medium risk), and red (high risk). Research reveals that the predictors of the classification of credit risk are most powerful for conscientiousness and neuroticism, with more conscientiousness equating to less risk and more neuroticism equating to more risk. Most of the customers are medium-risk, and more assessment is necessary prior to granting credit. The study reveals advantages of applying tests of psychology for making financial judgments, giving a better method to financial institutions than traditional financial standards for assessing creditworthiness. The approach enhances risk forecasting quality, assists with the minimization of non-performing.