Credit scoring models are developed to strengthen the decision-making process specifically
for financial institutions to deal with risk associated with a credit candidate while applying for …

Credit scoring (CS) is an effective and crucial approach used for risk management in banks
and other financial institutions. It provides appropriate guidance on granting loans and …

Credit scoring concerns with emerging empirical model to assist the financial institutions for
financial decision-making process. Credit risk analysis plays a vital role for decision-making …

The term credit scoring is extensively used in credit industries for decision making and
measuring the risk associated with an applicant. It uses applicants' historical data for credit …

Credit risk prediction is a critical task in the financial industry, allowing lenders to assess the
likelihood of a borrower defaulting on a loan. Traditional machine learning (ML) classifiers …

Credit scoring is a process of calculating the risk associated with an applicant on the basis of
applicant's credentials such as social status, financial status, etc. and it plays a vital role to …

In building a predictive credit scoring model, feature selection is an essential pre-processing
step that can improve the predictive accuracy and comprehensibility of models. In this study …

Credit scoring plays a vital role for financial institutions to estimate the risk associated with a
credit applicant applied for credit product. It is estimated based on applicants' credentials …

The credit scoring is a statistical analysis performed by financial institutions to represent the
creditworthiness of an individual or small and medium‐sized enterprise. A credit score is a …

Deep learning is a very important technique in clinical diagnosis and therapy in the present
world. Convolutional Neural Network (CNN) is a recent development in deep learning that is …