EARLY WARNING SYSTEM (AWS) ANALYSIS WITH THE LOGIT MODEL FOR PREDICTING THE CONSUMER LOAN BANKS (BPRs)

Abstract

The study with the title of “Early Warning System Analysis” is used to predict the Consumer Loan Banks’ potential bankruptcy. The samples are taken from the Consumer Loan Banks (BPR), publication by Bank Indonesia Financial Report, until October 2017, and from the very healthy BPRs with the assets of below twenty five billion rupiahs. The data are analyzed (1) by the use of descriptive quantitative technique to describe the samples (2) by means of correlation to find the relationship amongst the independent variables, that is, the eight financial ratios, and (3) by the use of probit regression to measure the accuracy of the model for predicting the BPR bankruptcy in Indonesia. The research concludes that (1) the Consumer Loan Banks (BPR), on average, have problems in capital, liquidity, operating cost, low-return asset, loan collectability, and low profitability, (2) the eight financial ratios have weak relation so that the regression model is made, (3) the financial ratios with positive impacts on predicting the BPR bankruptcy are NPL, LDR, BOPO, and CASH RATIO, whereas those with negative impacts are KPMM, ROA, PPAP, and ASSET. The level of accuracy of the estimated logit regression is 92.8%.