What question did this study set out to answer?

This study aims to analyze credit risk management dynamics in rural banks in Indonesia.

January 6, 2026Risks0 citationsOpen Access

Credit Risk Management Dynamics: Evidence from Indonesian Rural Banks

MAMoch Doddy AriefiantoBinus University TNTriasesiarta NurBinus University BMBryna MeivitawanliBinus University

Key Points

This study aims to analyze credit risk management dynamics in rural banks in Indonesia.
Utilized Panel Vector Autoregression to model relationships among key components.
Analyzed a dataset of 1461 rural banks in Indonesia from June 2010 to March 2024.
Explored components such as Non-Performing Loans, Loan Loss Provision, and loan charge-off.
Credit risk management predominantly follows an incurred loss approach.
Larger institutions tend to adopt the expected loss model more commonly.
Capital provides a critical buffer against credit losses.

Abstract

This paper investigates credit risk management as a dynamic system. Panel Vector Autoregression (PVAR) is employed to model interrelationships among four key components: Non-Performing Loans (NPLs), Loan Loss Provision (LLP), loan charge-off (LCO) and capital. The Cost-to-Income ratio (CIR) and Size and Net Profit-to-Equity ratio (ROE) are used as control variables. The panel dataset comprises 1461 conventional rural banks in Indonesia with a quarterly frequency from June 2010 to March 2024. There are several key findings of this study. First, credit risk management practices in rural banks predominantly follow an incurred loss approach, although the expected loss model appears to be more commonly adopted by larger institutions. Second, capital serves a critical function as a buffer against credit losses. Third, subsample investigation reveals a significant role of accounting discretionary. This study offers significant implications for both policy development and academic research in microfinance.

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