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

Author

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  • R'egis Houssou
  • J'er^ome Bovay
  • Stephan Robert

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.

Suggested Citation

  • R'egis Houssou & J'er^ome Bovay & Stephan Robert, 2019. "Adaptive Financial Fraud Detection in Imbalanced Data with Time-Varying Poisson Processes," Papers 1912.04308, arXiv.org.
    • Handle: RePEc:arx:papers:1912.04308
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    File URL: http://arxiv.org/pdf/1912.04308
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    References listed on IDEAS

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    4. Robert A. Jarrow & Stuart M. Turnbull, 2008. "Pricing Derivatives on Financial Securities Subject to Credit Risk," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 17, pages 377-409, World Scientific Publishing Co. Pte. Ltd..
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