FRAUD CUSTOMER PREDICTION BASED ON BANK LOAN DATA  ANALYSIS USING MACHINE LEARNING

Akansha Garg; Ankita Tiwari; Nagresh Kumar

FRAUD CUSTOMER PREDICTION BASED ON BANK LOAN DATA ANALYSIS USING MACHINE LEARNING

Authors: Akansha Garg , Ankita Tiwari, Nagresh Kumar

Unique Paper ID: 151525
Volume: 8
Issue: 1
PageNo: 211-215

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.

Download article

email to a friend

Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 1
PageNo: 211-215

FRAUD CUSTOMER PREDICTION BASED ON BANK LOAN DATA ANALYSIS USING MACHINE LEARNING

Available:https://ijirt.org/Article?manuscript=151525

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now