Adaptive Financial Fraud Detection in Imbalanced Data with Time-Varying Poisson Processes

R\'egis Houssou, J\'er\^ome Bovay and Stephan Robert

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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 the financial dataset shows a better predicting power than a baseline approach, especially in the case of higher imbalanced data.

Date: 2019-12
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1912.04308

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