International audienceThe application of classification models in the credit rating of banking customers has been investigated in the present paper. Credit rating is one of the main applications of data mining in the banking industry. The customers' creditworthiness can be evaluated through credit ratings. The data related to banking customers is very huge, and various classification techniques can be used to explore the hidden pattern and knowledge in data set through data mining. Several studies have been performed on the use of data mining and classification techniques in the credit rating of banking customers. After preparing and preprocessing the data using the C5 decision tree algorithm in this paper, the classification model has been...
A customer relationship management system is used to manage company relationships with current and p...
The enormous growth experienced by the credit industry has led researchers to develop sophisticated ...
In recent years there has been an increased adoption of data science methods in numerous fields and ...
Decision trees as one of the data mining techniques, is used in credit scoring of bank customers. Th...
For many years lenders have been using traditional statistical techniques such as logistic regressio...
The execution and outcome of credit rating policies of banks are highly relevant to banks' decisions...
This research study aims at using Data Mining and Fuzzy Logic approaches to classify the credit sco...
One of the primary concerns in most financial institutions to have an appropriate method for ranking...
Credit scoring model have been developed by banks and researchers to improve the process of assessin...
C4.5 is a learning algorithm that adopts local search strategy, and it cannot obtain the best decisi...
Today`s financial transactions have been increased through banks and financial institutions. Therefo...
A customer relationship management system is used to manage company relationships with current and p...
Banks are particularly exposed to credit risk due to the nature of their operations. Inadequate asse...
For many years lenders have been using traditional statistical techniques such as logistic regressio...
The enormous growth experienced by the credit industry has led researchers to develop sophisticated ...
A customer relationship management system is used to manage company relationships with current and p...
The enormous growth experienced by the credit industry has led researchers to develop sophisticated ...
In recent years there has been an increased adoption of data science methods in numerous fields and ...
Decision trees as one of the data mining techniques, is used in credit scoring of bank customers. Th...
For many years lenders have been using traditional statistical techniques such as logistic regressio...
The execution and outcome of credit rating policies of banks are highly relevant to banks' decisions...
This research study aims at using Data Mining and Fuzzy Logic approaches to classify the credit sco...
One of the primary concerns in most financial institutions to have an appropriate method for ranking...
Credit scoring model have been developed by banks and researchers to improve the process of assessin...
C4.5 is a learning algorithm that adopts local search strategy, and it cannot obtain the best decisi...
Today`s financial transactions have been increased through banks and financial institutions. Therefo...
A customer relationship management system is used to manage company relationships with current and p...
Banks are particularly exposed to credit risk due to the nature of their operations. Inadequate asse...
For many years lenders have been using traditional statistical techniques such as logistic regressio...
The enormous growth experienced by the credit industry has led researchers to develop sophisticated ...
A customer relationship management system is used to manage company relationships with current and p...
The enormous growth experienced by the credit industry has led researchers to develop sophisticated ...
In recent years there has been an increased adoption of data science methods in numerous fields and ...