FRAUD CUSTOMER PREDICTION BASED ON BANK LOAN DATA ANALYSIS USING MACHINE LEARNING
Author(s):
Akansha Garg , Ankita Tiwari, Nagresh Kumar
Keywords:
Accuracy score, Classification Report, F-score, Precision and Recall
Abstract
In our country, there has been a huge demand of personal loans arise from the citizens. There are so many people who are applying for the personal loan from banks as per their needs. But for the banks, it is difficult to detect the fraud customers that which customer will pay their loans & which will not due to the number of bank frauds is increasing day by day. To prevent this situation, we have explained how to create predictive loan models . In steps , we have shown how to process the raw data, select relevant features, performed data analysis & lastly built a model. In this paper, we have built some supervised learning models which are having higher accuracy score and on the basis of requests we easily determine which transactions to authorize. Classification report having higher f-score, precision and recall is considered as the best model among all the models.
Article Details
Unique Paper ID: 151525

Publication Volume & Issue: Volume 8, Issue 1

Page(s): 211 - 215
Article Preview & Download


Share This Article

Conference Alert

ICM - STEP

International conference on Management, Science, Technology, Engineering, Pharmact and Humanities.

Go To Issue



Call For Paper

Volume 7 Issue 9

Last Date 25 February 2020

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies