Data Mining Applications for Fraud Detection in Securities Market
- Koosha Golmohammadi
- Osmar R. Zaiane, University of Alberta (Database)
This paper presents an overview of fraud detection in securities market as well as a comprehensive literature review of data mining methods that are used to address the issue. We identify the best practices that are based on data mining methods for detecting known fraudulent patterns and discovering new predatory strategies. Furthermore, we highlight the challenges faced in the development and implementation of data mining systems for detecting market manipulation in securities market and we provide recommendation for future research works accordingly.
Citation
K. Golmohammadi, O. Zaiane. "Data Mining Applications for Fraud Detection in Securities Market". European Intelligence and Security Informatics Conference, Odense, Denmark, pp 107-114, August 2012.| Keywords: | data mining, fraud detection, securities market, market manipulation, stocks |
| Category: | In Conference |
| Web Links: | Proceedings |
BibTeX
@incollection{Golmohammadi+Zaiane:EISIC12,
author = {Koosha Golmohammadi and Osmar R. Zaiane},
title = {Data Mining Applications for Fraud Detection in Securities Market},
Pages = {107-114},
booktitle = {European Intelligence and Security Informatics Conference},
year = 2012,
}Last Updated: January 13, 2020Submitted by Sabina P
