Adaptive Financial Fraud Detection in Imbalanced Data with Time-Varying Poisson Processes
Risk Management
2019-12-11 v1
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.
Keywords
Cite
@article{arxiv.1912.04308,
title = {Adaptive Financial Fraud Detection in Imbalanced Data with Time-Varying Poisson Processes},
author = {Régis Houssou and Jérôme Bovay and Stephan Robert},
journal= {arXiv preprint arXiv:1912.04308},
year = {2019}
}
Comments
Accepted for publication in the Journal Of Financial Risk Management (JFRM). Comments welcome