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This study aims to analyze the level of accuracy of financial distress prediction models and to test the ability of liquidity risk ratio, credit risk and capital ratio in predicting the possibility of financial distress in rural banks (BPR) in Indonesia. The data used is sourced from secondary data and collected from BPR's financial statements published on the Financial Services Authority (OJK) website during the 2014-2023 period. The population in this study is all rural banks as many as 1,402 rural banks and the number of samples is 312 rural banks spread throughout Indonesia. Determination of samples by the Slovin method by proportionate stratified random sampling technique. The results of the study that the liquidity risk ratio, credit risk and capital ratio in predicting financial distress can be used with an accuracy rate of 95.90%. Liquidity risk ratio and credit risk ratio have a positive and significant effect, capital ratio and primary ratio have a negative and significant effect, while capital adequacy ratio has a positive and significant effect on the possibility of financial distress in rural banks in Indonesia.
Arsana et al. (Sat,) studied this question.