Clustering analysis and Datamining methodologies were applied to the problem of identifying illegal and fraud transactions. The researchers independently developed model and software using data provided by a bank and using Rapidminer modeling tool. The research objectives are to propose dynamic model and mechanism to cover fraud detection system limitations. KDA model as proposed model can detect 68.75% of fraudulent transactions with online dynamic modeling and 81.25% in offline mode and the Fraud Detection System & Decision Support System. Software propose a good supporting procedure to detect fraudulent transaction dynamically.
Cite
@article{arxiv.1503.03208,
title = {Fraudulent Electronic transaction detection using KDA Model},
author = {M. Vadoodparast and A. Razak Hamdan and Hafiz},
journal= {arXiv preprint arXiv:1503.03208},
year = {2015}
}