The primary goal of this study is to compare the performance of the Novel Random Forest
(RF) algorithm, Decision Tree (DT), and Logistic Regression in forecasting loan default (LR) …

With the improving banking sector in recent times and the increasing trend of taking loans, a
large population applies for bank loans. But one of the major problem banking sectors face …

How to effectively evaluate and identify the potential default risk of borrowers before issuing
loans and calculate the default probability of borrowers is the basis and important link of …

Credit risk management in modern financial organizations is based on assessing and
recognizing the potential default risk of borrowers prior to making loans and determining the …

As the core business of the banking system is to lend money and then get it back, loan
default is one of the most crucial issues for commercial banks. With data analysis and …

The growth of the country is significantly influenced by the bank. The overall economic and
financial health of any country directly affects a few of the services that the bank provides …

Loans are important products of financial institutions and banks. All institutions are trying to
find effective business strategies to convince more customers to apply for a loan. However …

Financial institutions that struggle with credit assessment can increase the accuracy and
efficacy of credit assessment by using techniques like broadening the data sources …

Lenders often experience loan defaults, resulting in huge losses to lenders. Lenders are
required to conduct a credit assessment of borrowers before making loans. Machine …

Loan lending plays an important role in our everyday life and powerfully promotes the
growth of consumption and the economy. Loan default has been unavoidable, which carries …