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Drazek, L. C. (2013). Intensity Estimation for Poisson Processes. Master Thesis, Leeds: The University of Leeds.

has been cited by the following article:

• 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.