Use of machine learning techniques in the prediction of credit recovery

, which proposes the construction of classifiers, based on the application of machine learning techniques, to identify defaulting clients with credit recovery potential. The study was carried out in 3 segments of a Bank's operations and achieved excellent results. Generalized linear modeling algorithms (GLM), distributed random forest algorithms (DRF), deep learning (DL) and gradient expansion algorithms (GBM) implemented on the H2O.ai platform were used.