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A DATA WAREHOUSE DESIGN FOR THE DETECTION OF FRAUD IN THE SUPPLY CHAIN BY USING THE BENFORD’S LAW

Title:

A DATA WAREHOUSE DESIGN FOR THE DETECTION OF FRAUD IN THE SUPPLY CHAIN BY USING THE BENFORD’S LAW

Kraus, Cornelia and Valverde, Raul (2014) A DATA WAREHOUSE DESIGN FOR THE DETECTION OF FRAUD IN THE SUPPLY CHAIN BY USING THE BENFORD’S LAW. American Journal of Applied Sciences, 11 (9). pp. 1507-1518. ISSN 1546-9239

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Official URL: http://thescipub.com/abstract/10.3844/ajassp.2014....

Abstract

Large data volumes and the inability to analyse them enables fraudulent activities to go unnoticed in supply chain management processes such as procurement, warehouse management and inventory management. This fraud increases the cost of the supply chain management and a fraud detection mechanism is necessary to reduce the risk of fraud in this business area. This study was carried out in order to develop a data warehouse design that supports forensic analytics by using the Benford’s law in order to detect fraud. The approach relies on a generic and re-usable store procedure for data analytics. The data warehouse was tested with two datasets collected from an operational supply chain database from the inventory management and warranty claims processes. The results of the research showed that the supply chain data analyzed obeys to Benford’s theory and that parameterized stored procedures with Dynamic SQL provide an excellent tool to analyze data in the supply chain for possible fraud detection. The implications of the results of the study are that the Benford’s law can be used to detect fraud in the supply chain with the help of parameterized stored procedures and a data ware house, this can ease the workload of the fraud analyst in the supply chain function. Although the research only used data from the inventory management and warranty claim processes, the proposed store procedures can be extended to any process in the supply chain making the results generalizable to the supply chain management process.

Divisions:Concordia University > John Molson School of Business > Decision Sciences and Management Information Systems
Item Type:Article
Refereed:Yes
Authors:Kraus, Cornelia and Valverde, Raul
Journal or Publication:American Journal of Applied Sciences
Date:7 July 2014
Funders:
  • Concordia Open Access Author Fund
Digital Object Identifier (DOI):10.3844/ajassp.2014.1507.1518
Keywords:Supply Chain Fraud, Supply Chain Management Systems, Benford’s law, Fraud Detection, Data Mining for Fraud, Accounting Information Systems
ID Code:978742
Deposited By: RAUL VALVERDE
Deposited On:23 Jul 2014 15:07
Last Modified:18 Jan 2018 17:47

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