Topics
machine learningDisease
UCIAgent
This paper aims to apply multiple machine learning algorithms to analyze the default payment of credit cards. By using the financial institution’s client data provided by UCI Machine Learning Repository, we will evaluate and compare the performance of the model candidates in order to choose the most robust model. Moreover, we will also decide which are important features in our best predictive model
As profitable customer acquisition becomes more and more critical for the banking sector in terms of...
In the banking sector, every banking infrastructure contains an enormous dataset for customers’ cred...
Presently, the use of a credit card has become an integral part of contemporary banking and financia...
The purpose of this research is to compare seven machine learning methods to predict customer’s cred...
Credit card defaults pause a business-critical threat in banking systems thus prompt detection of de...
The ability of financial institutions to detect whether a customer will default on their credit card...
Credit risk as the board in banks basically centers around deciding the probability of a customer's ...
This paper is an extended version of the paper originally presented at the International Conference ...
Credit risk plays a major role in the banking industry business. Banks' main activities involve gran...
This master thesis explore the potential of Machine Learning techniques in predicting default of veh...
In this master thesis we apply a variation of different machine learning techniques on a dataset for...
Financial threats are displaying a trend about the credit risk of commercial banks as the incredible...
Giving credit is one of the core businesses in banking and the importance of credit risk management ...
Creditinfo collects information about claims that go through their claim collection system. The goal...
Data mining and Machine learning are the emerging technologies that are rapidly spreading in every f...
As profitable customer acquisition becomes more and more critical for the banking sector in terms of...
In the banking sector, every banking infrastructure contains an enormous dataset for customers’ cred...
Presently, the use of a credit card has become an integral part of contemporary banking and financia...
The purpose of this research is to compare seven machine learning methods to predict customer’s cred...
Credit card defaults pause a business-critical threat in banking systems thus prompt detection of de...
The ability of financial institutions to detect whether a customer will default on their credit card...
Credit risk as the board in banks basically centers around deciding the probability of a customer's ...
This paper is an extended version of the paper originally presented at the International Conference ...
Credit risk plays a major role in the banking industry business. Banks' main activities involve gran...
This master thesis explore the potential of Machine Learning techniques in predicting default of veh...
In this master thesis we apply a variation of different machine learning techniques on a dataset for...
Financial threats are displaying a trend about the credit risk of commercial banks as the incredible...
Giving credit is one of the core businesses in banking and the importance of credit risk management ...
Creditinfo collects information about claims that go through their claim collection system. The goal...
Data mining and Machine learning are the emerging technologies that are rapidly spreading in every f...
As profitable customer acquisition becomes more and more critical for the banking sector in terms of...
In the banking sector, every banking infrastructure contains an enormous dataset for customers’ cred...
Presently, the use of a credit card has become an integral part of contemporary banking and financia...
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