Mehta, Priya and Mathews, Jithin and Ch, Sobhan Babu et. al.
(2017)
A Graph Theoretical Approach for Identifying Fraudulent Transactions in Circular Trading.
In: DATA ANALYTICS 2017 : The Sixth International Conference on Data Analytics, Barcelona.
Abstract
Circular trading is an infamous technique used by tax evaders to confuse tax enforcement officers from detecting suspicious transactions. Dealers using this technique superimpose suspicious transactions by several illegitimate sales transactions in a circular manner. In this paper, we address this problem by developing an algorithm that detects circular trading and removes the illegitimate cycles to uncover the suspicious transactions. We formulate the problem as finding and then deleting specific type of cycles in a directed edge-labeled multigraph. We run this algorithm on the commercial tax data set provided by the government of Telangana, India, and discovered several suspicious transactions.
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