Author(s)

Régis Houssou¹, Jérôme Bovay², Stephan Robert¹

¹School of Management and Engineering Vaud (HEIG-VD), Yverdon-les-Bains, Switzerland.
²NetGuardians SA, Yverdon-les-Bains, Switzerland.

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.

Homogeneous Poisson Process, Inhomogeneous Poisson Process, Intensity Model, Fraud Detection, Imbalanced Data

Houssou, R. , Bovay, J. and Robert, S. (2019) Adaptive Financial Fraud Detection in Imbalanced Data with Time-Varying Poisson Processes. Journal of Financial Risk Management, 8, 286-304. doi: 10.4236/jfrm.2019.84020.