GraphGuard: Contrastive Self-Supervised Learning for Credit-Card Fraud Detection in Multi-Relational Dynamic Graphs

Fuente: arXiv
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Bibliographic Details
Main Authors: Reynisson, Kristófer, Schreyer, Marco, Borth, Damian
Format: Preprint
Published: 2024
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author Reynisson, Kristófer
Schreyer, Marco
Borth, Damian
author_facet Reynisson, Kristófer
Schreyer, Marco
Borth, Damian
contents Credit card fraud has significant implications at both an individual and societal level, making effective prevention essential. Current methods rely heavily on feature engineering and labeled information, both of which have significant limitations. In this work, we present GraphGuard, a novel contrastive self-supervised graph-based framework for detecting fraudulent credit card transactions. We conduct experiments on a real-world dataset and a synthetic dataset. Our results provide a promising initial direction for exploring the effectiveness of graph-based self-supervised approaches for credit card fraud detection.
format Preprint
id arxiv_https___arxiv_org_abs_2407_12440
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle GraphGuard: Contrastive Self-Supervised Learning for Credit-Card Fraud Detection in Multi-Relational Dynamic Graphs
Reynisson, Kristófer
Schreyer, Marco
Borth, Damian
Machine Learning
Credit card fraud has significant implications at both an individual and societal level, making effective prevention essential. Current methods rely heavily on feature engineering and labeled information, both of which have significant limitations. In this work, we present GraphGuard, a novel contrastive self-supervised graph-based framework for detecting fraudulent credit card transactions. We conduct experiments on a real-world dataset and a synthetic dataset. Our results provide a promising initial direction for exploring the effectiveness of graph-based self-supervised approaches for credit card fraud detection.
title GraphGuard: Contrastive Self-Supervised Learning for Credit-Card Fraud Detection in Multi-Relational Dynamic Graphs
topic Machine Learning
url https://arxiv.org/abs/2407.12440