Financial fraud: Data mining application and detection

被引:0
|
作者
Aziz, N. H. A. [1 ,2 ]
Zakaria, N. B. [1 ,2 ]
Mohamed, I. S. [1 ,2 ]
机构
[1] Univ Teknol MARA, Accounting Res Inst, Segamat Campus, Shah Alam, Malaysia
[2] Univ Teknol MARA, Fac Accountancy, Shah Alam, Malaysia
关键词
PREVENTION;
D O I
暂无
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
This paper reviews the data mining application and detection on financial fraud. This study also discuss the fundamental idea of financial fraud and the application of data mining in financial fraud detection. Moreover this study also provides a deep understanding on the merits and drawbacks of the data mining application in detecting financial fraud. The sources of data collected include documents and text specifically from journals, authors review and a comparison analysis on merits and drawbacks of data mining. Data mining is proven to be reliable with high accuracy. Nonetheless the issues of privacy and security are the two main concerns in data mining application.
引用
收藏
页码:341 / 344
页数:4
相关论文
共 50 条
  • [1] A taxonomy to guide research on the application of data mining to fraud detection in financial statement audits
    Gray, Glen L.
    Debreceny, Roger S.
    [J]. INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS, 2014, 15 (04) : 357 - 380
  • [2] Data Mining Approach In Financial Fraud Detection and a Literature Review
    Esen, M. Fevzi
    [J]. ESKISEHIR OSMANGAZI UNIVERSITESI IIBF DERGISI-ESKISEHIR OSMANGAZI UNIVERSITY JOURNAL OF ECONOMICS AND ADMINISTRATIVE SCIENCES, 2016, 11 (02): : 93 - 118
  • [3] Research on the Detection of Financial Fraud Using Data Mining Techniques
    Li Yanling
    Li Nan
    Yang Mingpei
    [J]. PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON ADVANCED DESIGN AND MANUFACTURING ENGINEERING (ICADME 2017), 2017, 136 : 473 - 481
  • [4] The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature
    Ngai, E. W. T.
    Hu, Yong
    Wong, Y. H.
    Chen, Yijun
    Sun, Xin
    [J]. DECISION SUPPORT SYSTEMS, 2011, 50 (03) : 559 - 569
  • [5] Fraud detection in financial statements using data mining and GAN models
    Aftabi, Seyyede Zahra
    Ahmadi, Ali
    Farzi, Saeed
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2023, 227
  • [6] Prevention and Detection of Financial Statement Fraud - An Implementation of Data Mining Framework
    Gupta, Rajan
    Gill, Nasib Singh
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2012, 3 (08) : 150 - 156
  • [7] Integrating Data Mining Techniques for Fraud Detection in Financial Control Processes
    Sushkov, Viktor M.
    Leonov, Pavel Y.
    Nadezhina, Olga S.
    Blagova, Irina Y.
    [J]. INTERNATIONAL JOURNAL OF TECHNOLOGY, 2023, 14 (08): : 1675 - 1684
  • [8] A Review of Data Mining-based Financial Fraud Detection Research
    Yue, Dianmin
    Wu, Xiaodan
    Wang, Yunfeng
    Li, Yue
    Chu, Chao-Hsien
    [J]. 2007 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-15, 2007, : 5519 - +
  • [9] DATA MINING APPLICATION IN CREDIT CARD FRAUD DETECTION SYSTEM
    Ogwueleka, Francisca Nonyelum
    [J]. JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY, 2011, 6 (03): : 311 - 322
  • [10] A Distributed Approach of Big Data Mining for Financial Fraud Detection in a Supply Chain
    Zhou, Hangjun
    Sun, Guang
    Fu, Sha
    Fan, Xiaoping
    Jiang, Wangdong
    Hu, Shuting
    Li, Lingjiao
    [J]. CMC-COMPUTERS MATERIALS & CONTINUA, 2020, 64 (02): : 1091 - 1105