Probabilistic Prediction of the Financial Performance of Conventional and Islamic Banks During the Covid-19 Pandemic

Abstract

This study aims to predict the probability of achieving the financial performance of conventional and Islamic banks listed on the Indonesia Stock Exchange during the Covid-19 pandemic. This study uses Return on Assets (ROA) as the dependent variable, E-Banking implementation variables; FinTech growth, GDP growth; inflation; interest rates; Capital Adequacy Ratio (CAR), Non Performing Loan (NPL) and Non Performing Financing (NPF); Operating Expenses to Operating Income (BOPO) as independent variables. This study uses correlational research with a quantitative approach. The research sample consists of 47 banks listed on the Indonesia Stock Exchange, with 43 banks operating conventionally and 4 banks operating sharia. Documentation and literature study methods were used to collect data which were then analyzed using logistic regression. The results showed that the variables that are able to predict the probability of ROA occurrence in conventional banking are the application of E-Banking, NPL (n) and BOPO, while in Islamic banking the variables of FinTech growth, Inflation and BOPO are variables that are able to predict the probability of ROA occurrence.