Credit Card Fraud Detection System using Visual Analytics through the Data Mining
Author(s):
J. Gayathri, Mylapoore Madhu
Keywords:
Visual Knowledge Discovery, Data Mining, Financial Visualization, Financial Fraud Detection.
Abstract
Financial institutions are interested in ensuring security and quality for their customers. Banks, for instance, need to identify and stop harmful transactions in a timely manner. In order to detect fraudulent operations, data mining techniques and customer profile analysis are commonly used. Thus, we propose EVA, a Visual Analytics approach for supporting fraud investigation, fine-tuning fraud detection algorithms, and thus, reducing false positive alarms. Due to the theatrical increases of fraud which results in loss of dollars worldwide each year, several modern techniques in detecting fraud are persistently evolved and applied to many business fields. The goal of this paper is to provide a security in credit card transaction using EVA technique to detect fraud. The credit card fraud detection features uses user behavior and location scanning to check for unusual patterns.
Article Details
Unique Paper ID: 145940
Publication Volume & Issue: Volume 4, Issue 11
Page(s): 788 - 793
Article Preview & Download
Share This Article
Join our RMS
Conference Alert
NCSEM 2024
National Conference on Sustainable Engineering and Management - 2024