A Graph Says More than a Thousand Journal Entries - Harnessing Graph Autoencoder Networks in Auditing

Journal
Expert Focus
Type
journal article
Date Issued
2024-12-01
Author(s)
Huang, Qing
;
;
Michiles Junior Nilson Romero
;
Miklos A. Vasarhelyi
Abstract
The integration of artificial intelligence into auditing opens up new pathways. By in terpreting journal entries through the innovative lens of graphs, auditors are able to uncover complex accounting patterns and anomalies. This article illustrates how graph representation learning-based auditing can be applied in practice through two practical case studies.
Language
English
Keywords
Auditing
Artificial Intelligence
Deep Learning
Fraud Detection
HSG Classification
contribution to practical use / society
Refereed
Yes
Publisher
EXPERTsuisse
Publisher place
Zurich
Volume
2024
Number
12
Start page
653
End page
659
Pages
7
URL
Subject(s)

business studies

Division(s)

ICS - Institute of Co...

Contact Email Address
marco.schreyer@unisg.ch
File(s)
Thumbnail Image

open.access

Name

2024_12_01_A_Graph_Says_More_than_a_Thousand_Journal_Entries.pdf

Size

387.29 KB

Format

Adobe PDF

Checksum (MD5)

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