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A Graph Theoretical Approach for Identifying Fraudulent Transactions in Circular Trading

Authors:
Priya Mehta
Jithin Mathews
S.V. Kasi Visweswara Rao
K. Sandeep Kumar
Ch. Sobhan Babu

Keywords: social network analysis; fraud detection; circular trading; value added tax

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 dataset provided by the government of Telangana, India, and discovered several suspicious transactions.

Pages: 28 to 33

Copyright: Copyright (c) IARIA, 2017

Publication date: November 12, 2017

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-603-3

Location: Barcelona, Spain

Dates: from November 12, 2017 to November 16, 2017