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Adaptive Financial Fraud Detection in Imbalanced Data with Time-Varying Poisson Processes
School of Management and Engineering Vaud (HEIG-VD), Yverdon-les-Bains, Switzerland
NetGuardians SA, Yverdon-les-Bains, Switzerland
School of Management and Engineering Vaud (HEIG-VD), Yverdon-les-Bains, Switzerland
- 1 School of Management and Engineering Vaud (HEIG-VD), Yverdon-les-Bains, Switzerland
- 2 NetGuardians SA, Yverdon-les-Bains, Switzerland
- 3 School of Management and Engineering Vaud (HEIG-VD), Yverdon-les-Bains, Switzerland
Journal of Financial Risk Management·Volume 08 (2019)·Pages 286–304·Published 19 November 2019·DOI10.4236/jfrm.2019.84020
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Abstract
This paper discusses financial fraud detection in imbalanced dataset using homogeneous and non-homogeneous Poisson processes. The probability of predicting fraud on the financial transaction is derived. Applying our methodology to financial datasets with different fraud profiles shows a better predicting power than a baseline approach, especially in the case of higher imbalanced data.
KeywordsHomogeneous Poisson ProcessInhomogeneous Poisson ProcessIntensity ModelFraud DetectionImbalanced Data
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