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.
Highlights
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
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
Summary
Cornelia Kraus and Raul Valverde / American Journal of Applied Sciences 11 (9): 1507-1518, 2014 develop a data warehouse design to support analytics, reporting and data mining and forensic analytics by using the Benford’s law within the area of supply chain This is to detect fraud or to point out data anomalies that are worth further examination by subject matter experts. The detailed fraud report of 2008 points out that especially the increasing demand for natural resources often forced to act fast, exploring new sites, setting them up for production and find supplier and logistic companies to provide energy, staff and the like As these sites are often in remote areas, the number of available suppliers are quite limited and this might lead responsible managers into situations where “flexibility” and the need to “make things happen” cause non-legal or at least questionable actions. Dependency on one supplier, conflict of interest or bribery may be some of those actions taken (Kroll Advisory, 2010)
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