Research Article
Classification and Fraud Detection in Finance Industry
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 176 - Issue 3 |
| Published: Oct 2017 |
| Authors: Akshansh Sinha, Shivam Mokha |
10.5120/ijca2017915570
|
Akshansh Sinha, Shivam Mokha . Classification and Fraud Detection in Finance Industry. International Journal of Computer Applications. 176, 3 (Oct 2017), 45-52. DOI=10.5120/ijca2017915570
@article{ 10.5120/ijca2017915570,
author = { Akshansh Sinha,Shivam Mokha },
title = { Classification and Fraud Detection in Finance Industry },
journal = { International Journal of Computer Applications },
year = { 2017 },
volume = { 176 },
number = { 3 },
pages = { 45-52 },
doi = { 10.5120/ijca2017915570 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2017
%A Akshansh Sinha
%A Shivam Mokha
%T Classification and Fraud Detection in Finance Industry%T
%J International Journal of Computer Applications
%V 176
%N 3
%P 45-52
%R 10.5120/ijca2017915570
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Due to increase of fraud which results in loss of money across the globe, several methodologies and techniques developed for detecting frauds Fraud detection involves analysing the activities of users in order to understand the malicious behaviour of users. Malicious behaviour is a broad term including delinquency, fraud, intrusion, and account defaulting. This paper presents a survey of current techniques used in credit card fraud detection and evaluates a new hybrid approach to identify fraud detection. The paper also discusses popular algorithms used for unsupervised and supervised learning.
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