TITLE:
Adaptive Financial Fraud Detection in Imbalanced Data with Time-Varying Poisson Processes
AUTHORS:
Régis Houssou, Jérôme Bovay, Stephan Robert
KEYWORDS:
Homogeneous Poisson Process, Inhomogeneous Poisson Process, Intensity Model, Fraud Detection, Imbalanced Data
JOURNAL NAME:
Journal of Financial Risk Management,
Vol.8 No.4,
December
30,
2019
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.