In this paper, we use a stacking ensemble to construct a bankruptcy prediction model. We
collect a comprehensive list of 40 financial ratios (FRs) and 21 corporate governance …

Loan default is a serious problem in banking industries. Banking systems have strong
processes in place for identification of customers with poor credit risk scores; however, most …

In addition to the advantages of the digital world, there are also disadvantages, which can
harm people. With the spread of credit cards with the digital transformation, banks have …

Some researchers find data with imbalanced class conditions, where there are data with a
number of minorities and a majority. SMOTE is a data approach for an imbalanced classes …

Credit scoring attracts special attention of financial institutions. In recent years, deep
learning methods have been particularly interesting. In this paper, we compare the …

Background: The typical approach to identify blood-derived gene expression signatures as a
biomarker for Alzheimer's disease (AD) have relied on training classification models using …

Over the past decades, financial institutions have been giving increased importance to credit
risk management as a critical tool to control their profitability. More than ever, it became …

Context. The problem of credit assessment of a client is considered. It is a simultaneous
processing of lender's data of different nature with further definition of the credit rating. The …

One of the major developments in machine learning in the past decade is the ensemble
method, which finds highly accurate classifier by combining many moderately accurate …

IMPROVING THE QUALITY OF CREDIT ACTIVITY BY USING SCORING MODEL Page 1 e-ISSN
1607-3274 Радіоелектроніка, інформатика, управління. 2019. № 2 p-ISSN 2313-688X …