This paper is published in Volume-6, Issue-5, 2020
Area
CSE
Author
Manpreet Kaur
Co-authors
Gurinderpal Singh
Org/Univ
Institute of Engineering and Technology, Bhaddal, Punjab, India
Pub. Date
22 September, 2020
Paper ID
V6I5-1208
Publisher
Keywords
Credit Card, Financial, DecisionTree, DataMining, Prediction

Citationsacebook

IEEE
Manpreet Kaur, Gurinderpal Singh. Calculation of client credit risk prediction in banking sector using data mining, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Manpreet Kaur, Gurinderpal Singh (2020). Calculation of client credit risk prediction in banking sector using data mining. International Journal of Advance Research, Ideas and Innovations in Technology, 6(5) www.IJARIIT.com.

MLA
Manpreet Kaur, Gurinderpal Singh. "Calculation of client credit risk prediction in banking sector using data mining." International Journal of Advance Research, Ideas and Innovations in Technology 6.5 (2020). www.IJARIIT.com.

Abstract

The use of credit scoring can be used to assist the analysis of credit risk in assessing the eligibility of the applicant. As a valuable method for credit rating, data mining has been proven. Many credit scoring models for determining the creditworthiness of loan applicants have been established over the last few years. With an obligation to repay over a period of time, credit provides access to capital today, There may be financial sources, or they may consist of goods or services. Today, credit has become a very necessary component of daily life. Although credit cards are currently the most common type of loan, other credit plans include, among others, residential mortgages, car loans, student loans, small business loans, commercial lending, and bonds.
Paper PDF