ANALISIS PENGARUH PERKEMBANGAN FINTECH LENDING TERHADAP KINERJA PERBANKAN

Bank is a financial institution whose business activities are collecting funds from the public and channeling these funds back to the community and providing other services. The purpose of this study is to find out what factors can affect ROA on Fintech Lending. The object of this research is the number of lenders (JL), the number of borrowers (JB) and the number of loans (JP). The data used in this study is secondary data obtained from Bank Indonesia and the Financial Services Authority. The data sample used is the Fintech Lending statistical report in the period July 2018 – September 2021. The analytical method used is the Error Correction Model (ECM) analysis method. Based on the analysis that has been done, it can be seen that the JL variable in the short term has a positive but not significant effect on ROA with a coefficient of 0.214752 and a probability of 0.6288. And in the long term a significant positive effect on ROA with a coefficient of 0.858246 and a probability of 0.0000. The variable JB in the short term has a positive but not significant effect on ROA with a coefficient of 0.562269 and a probability of 0.2093. And in the long term it has a positive but not significant effect on ROA with a coefficient of 0.485957 and a probability of 0.0988. The variable JP in the short term has a negative but not significant effect on ROA with a coefficient of - 0.458719 and a probability of 0.4593. And in the long term it has a negative but not significant effect on ROA with a coefficient of -0.974243 and a probability of 0.0076.