USING BIG DATA IN INTERNAL FRAUD DETECTION

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TIDE AcademIA Research
Volume:3 Issue:1
USING BIG DATA IN INTERNAL FRAUD DETECTION

USING BIG DATA IN INTERNAL FRAUD DETECTION

Authors : Teoman Samet TEMUÇİN, Sefa ERBAŞ, Anıl AY

Pages : 55-82

View : 15 | Download : 11

Publication Date : 2021-07-31

Article Type : Research Paper

Abstract :Internal frauds are one of the most important operational risks threating entities. In addition to significant operational loss, they also cause reputational and prestige loss. Therefore, in addition to preventive proactive controls, the existence of deterrent practices to quickly detect them is of great importance. In this paper, we will tell transformation story of Garanti BBVA Internal Audit Department regarding the detection of internal frauds made through the use of big data capabilities. We will talk about how the previous detection method called as “scenario-based” has been converted into the new detection approach called as “rule-based” with the more effective use of big data capabilities. This new detection method has allowed provision of assurance to a higher number of risky transactions with the same resources, achievement of a significant increase rate in the detection of internal frauds and decrease in the loss incurred due to internal frauds. We hope that this new methodology which has proven its success in the fields of efficiency and effectiveness will also be a source of inspiration for the sector.
Keywords : internal fraud, fraud detection, big data

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