Comparative Study of Data Mining Model for Credit Card Application Scoring in Bank
نویسنده
چکیده
The growth of credit card application needs to be balanced with the anticipation of bad credit risk because it does not use security collateral as warranty. The usage of credit scoring can be used to help the credit risk analysis in determining the applicant's eligibility. Data mining has been proven as a valuable tool for credit scoring. The aim of this research is to design a data mining model for credit scoring in bank in order to support and improve the performance of the credit analyst job. The proposed model applies classification using Naïve Bayes and ID3 algorithm. The accuracy of Naïve Bayes classifier is 82% and ID3 is 76%. So we can conclude that Naïve Bayes classifier has better accuracy than ID3 classifier.
منابع مشابه
Personal Credit Score Prediction using Data Mining Algorithms (Case Study: Bank Customers)
Knowledge and information extraction from data is an age-old concept in scientific studies. In industrial decision-making processes, the application of this concept gives rise to data-mining opportunities. Personal credit scoring is an ever-vital tool for banking systems in order to manage and minimize the inherent risks of the financial sector, thus, the design and improvement of credit scorin...
متن کاملComparative Analysis of Data Reduction Model for Credit Scoring
The development of credit card application should be in proportion with the expectation of terrible credit hazard on the grounds that it doesn't utilize security collateral as guarantee. The use of credit scoring can be utilized to help the credit hazard assay in deciding the customer's eligibility. Data mining has been demonstrated as a significant tool for credit scoring. The objective of thi...
متن کاملUsing the Hybrid Model for Credit Scoring (Case Study: Credit Clients of microloans, Bank Refah-Kargeran of Zanjan, Iran)
In any country, commercial banks lay the groundwork for economic growth by collecting national resources and capitals and allocating them to different economic sectors. Optimal allocation of resources is especially important in achieving this goal. Banks with an effective and dynamic system of customer assessment can efficiently allocate their resources to customers regardless of their geograph...
متن کاملDetecting Suspicious Card Transactions in unlabeled data of bank Using Outlier Detection Techniqes
With the advancement of technology, the use of ATM and credit cards are increased. Cyber fraud and theft are the kinds of threat which result in using these Technologies. It is therefore inevitable to use fraud detection algorithms to prevent fraudulent use of bank cards. Credit card fraud can be thought of as a form of identity theft that consists of an unauthorized access to another person's ...
متن کاملFeature Selection in Credit Scoring Model for Credit Card Applicants in XYZ Bank: A Comparative Study
The performance of credit scoring models is determined by the used features. The relevant features for credit scoring usually are determined unsystematic and dominate by arbitrary trial. This paper presents a comparative study of four feature selection methods, which use data mining approach in reducing the feature space. The final results show that among the four feature selection methods, the...
متن کامل