arXiv Artificial Intelligence

Temporal Heterogeneous Graph Transformer for Credit Card Fraud Detection

8 hours ago 10.09.2026 07:00 👁 1 views
Temporal Heterogeneous Graph Transformer for Credit Card Fraud Detection

Quick summary

arXiv:2609.07100v1 Announce Type: cross Abstract: Credit card fraud detection typically relies on tabular features, while repeated attributes can also provide useful relational signals. This paper proposes THGT-FD, a Temporal Heterogeneous Graph Transformer for Fraud Detection. Each transaction is represented using one transaction token and six types of relation tokens and incorporates Time2Vec encoding into the transaction representation. A Transformer learns the interactions among these tokens within each individual transaction and then outputs a fraud probability. Experiments were conducted

Key takeaways

  • arXiv:2609.07100v1 Announce Type: cross Abstract: Credit card fraud detection typically relies on tabular features, while repeated attributes can also provide useful relational signals.
  • This paper proposes THGT-FD, a Temporal Heterogeneous Graph Transformer for Fraud Detection.
  • Each transaction is represented using one transaction token and six types of relation tokens and incorporates Time2Vec encoding into the transaction representation.

Why it matters

“Temporal Heterogeneous Graph Transformer for Credit Card Fraud Detection” shows why AI risk cannot be reduced to answer accuracy. Access controls, logging, human approval and incident response need to be designed into the workflow from the start.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗