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A Survey on Financial Fraud Detection Methodologies

by Pankaj Richhariya, Prashant K Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 22
Year of Publication: 2012
Authors: Pankaj Richhariya, Prashant K Singh
10.5120/7080-9373

Pankaj Richhariya, Prashant K Singh . A Survey on Financial Fraud Detection Methodologies. International Journal of Computer Applications. 45, 22 ( May 2012), 15-22. DOI=10.5120/7080-9373

@article{ 10.5120/7080-9373,
author = { Pankaj Richhariya, Prashant K Singh },
title = { A Survey on Financial Fraud Detection Methodologies },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 22 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 15-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number22/7080-9373/ },
doi = { 10.5120/7080-9373 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:38:14.942334+05:30
%A Pankaj Richhariya
%A Prashant K Singh
%T A Survey on Financial Fraud Detection Methodologies
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 22
%P 15-22
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Owing to levitate and rapid escalation of E-Commerce, cases of financial fraud allied with it are also intensifying and which results in trouncing of billions of dollars worldwide each year. Fraud detection involves scrutinizing the behavior of populations of users in order to ballpark figure, detect, or steer clear of objectionable behavior: Undesirable behavior is a extensive term including delinquency: swindle, infringement, and account evasion. Factually, swindle transactions are speckled with genuine transactions and simple pattern matching techniques are not often sufficient to detect those frauds accurately. In this survey we, will focuses on classifying fraudulent behaviors, identifying the major sources and characteristics of the data based on which fraud detection has been conducted. This paper provide a comprehensive survey and review of different techniques to detect the financial fraud detection used in various fraud like credit card fraud detection, online auction fraud, telecommunication fraud detection, and computer intrusion detection.

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Index Terms

Computer Science
Information Sciences

Keywords

Fraud Detection Data Mining Neural Network

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