MACROECONOMIC DETERMINANTS OF NON-PERFORMING LOANS IN INDONESIA'S PEER-TO-PEER LENDING SECTOR

Abstract

The emergence of peer-to-peer (P2P) lending as a fintech innovation in Indonesia’s digital financial ecosystem has played a pivotal role in reshaping credit distribution, yet it has also coincided with a notable rise in non-performing loans (NPLs). While much of the existing literature focuses on traditional banking sectors, this study introduces a novel approach by concentrating exclusively on P2P lending—a relatively under-researched domain in Indonesia—in relation to macroeconomic dynamics. Specifically, it quantitatively investigates the impact of key macroeconomic indicators—economic growth, the benchmark interest rate (BI Rate), and the unemployment rate—on the occurrence of NPLs within P2P platforms. Utilizing quarterly time series data spanning from Q1 2020 to Q4 2024, sourced from Statistics Indonesia (BPS) and the Financial Services Authority (OJK), the study employs multiple linear regression analysis. The findings reveal that the three macroeconomic variables jointly exert a statistically significant effect on NPLs (F-test = 0.002). However, on an individual basis, only economic growth demonstrates a significant negative influence (p = 0.000), whereas the BI Rate and unemployment rate do not yield significant effects (p = 0.208 and 0.488, respectively). This research underscores the heightened sensitivity of P2P lending to shifts in economic performance and contributes to the academic discourse by highlighting the importance of developing adaptive, fintech-specific credit risk models in response to evolving macroeconomic conditions.