The information-mathematical system of the borrower’s solvency prediction

The paper is about research of the algorithms, methods of the classification and prediction objects’ groups, depiction of the informationmathematical system, which is created on these algorithms’ basis. They use variety methods of the machine learning and their compilations – aggregative classifier, all of these is for the solution of the classification’s problem, particularly borrower’s solvency prediction. This helps to make previous preparation of the source data, which also contents discretisation, missed data’s recovery and detection of the important factors for statistics, how to use these methods of the classification and create cogeneration models, how to analyze quality of these models using statistical measures, to predict objects’ groups.